{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fruit_label</th>\n",
       "      <th>fruit_name</th>\n",
       "      <th>fruit_subtype</th>\n",
       "      <th>mass</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>color_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>192</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>180</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>176</td>\n",
       "      <td>7.4</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>86</td>\n",
       "      <td>6.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>84</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fruit_label fruit_name fruit_subtype  mass  width  height  color_score\n",
       "0            1      apple  granny_smith   192    8.4     7.3         0.55\n",
       "1            1      apple  granny_smith   180    8.0     6.8         0.59\n",
       "2            1      apple  granny_smith   176    7.4     7.2         0.60\n",
       "3            2   mandarin      mandarin    86    6.2     4.7         0.80\n",
       "4            2   mandarin      mandarin    84    6.0     4.6         0.79"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits = pd.read_table('fruit_data_with_colors.txt')\n",
    "fruits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 'apple', 2: 'mandarin', 3: 'orange', 4: 'lemon'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a mapping from fruit label value to fruit name to make results easier to interpret\n",
    "look_up_fruit_name = dict(zip(fruits.fruit_label.unique(), fruits.fruit_name.unique()))\n",
    "look_up_fruit_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(59, 7)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Split the data into training and testing\n",
    "X = fruits[['mass', 'width', 'height', 'color_score']]\n",
    "y = fruits['fruit_label']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 0)\n",
    "\n",
    "# plotting a scatter matrix\n",
    "from matplotlib import cm\n",
    "cmap = cm.get_cmap('gnuplot')\n",
    "scatter = pd.plotting.scatter_matrix(X_train, c = y_train, marker = 'o', s=40, hist_kwds={'bins':15}, figsize=(9,9), cmap = cmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting a 3D scatter plot\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection = '3d')\n",
    "ax.scatter(X_train['width'], X_train['height'], X_train['color_score'], c = y_train, marker = 'o', s=100)\n",
    "ax.set_xlabel('width')\n",
    "ax.set_ylabel('height')\n",
    "ax.set_zlabel('color_score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = fruits[['mass', 'width', 'height']]\n",
    "y = fruits['fruit_label']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create classifier object\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "knn = KNeighborsClassifier(n_neighbors = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n",
       "                     weights='uniform')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the classifier using the training data\n",
    "knn.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5333333333333333"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Estimate the accuracy of the classifier on future data, using the test data\n",
    "knn.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'mandarin'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use the trained k-NN classifier model to classify new, previously unseen objects\n",
    "# first example: a small fruit with mass 20g, width 4.3 cm, height 5.5 cm\n",
    "fruit_prediction = knn.predict([[20, 4.3, 5.5]])\n",
    "look_up_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'lemon'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruit_prediction = knn.predict([[100, 6.3, 8.5]])\n",
    "look_up_fruit_name[fruit_prediction[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\python数据分析\\susanli-python\\Machine-Learning-with-Python-master\\adspy_shared_utilities.py:172: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  X_mat = X[['height', 'width']].as_matrix()\n",
      "D:\\python数据分析\\susanli-python\\Machine-Learning-with-Python-master\\adspy_shared_utilities.py:173: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  y_mat = y.as_matrix()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the decision boundries of the k-NN classifier\n",
    "from adspy_shared_utilities import plot_fruit_knn\n",
    "plot_fruit_knn(X_train, y_train, 5, 'uniform')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\python数据分析\\susanli-python\\Machine-Learning-with-Python-master\\adspy_shared_utilities.py:172: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  X_mat = X[['height', 'width']].as_matrix()\n",
      "D:\\python数据分析\\susanli-python\\Machine-Learning-with-Python-master\\adspy_shared_utilities.py:173: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  y_mat = y.as_matrix()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_fruit_knn(X_train, y_train, 1, 'uniform')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\python数据分析\\susanli-python\\Machine-Learning-with-Python-master\\adspy_shared_utilities.py:172: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  X_mat = X[['height', 'width']].as_matrix()\n",
      "D:\\python数据分析\\susanli-python\\Machine-Learning-with-Python-master\\adspy_shared_utilities.py:173: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  y_mat = y.as_matrix()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_fruit_knn(X_train, y_train, 10, 'uniform')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x247a92555f8>,\n",
       "  <matplotlib.axis.XTick at 0x247a9254080>,\n",
       "  <matplotlib.axis.XTick at 0x247a9254470>,\n",
       "  <matplotlib.axis.XTick at 0x247a9253240>,\n",
       "  <matplotlib.axis.XTick at 0x247a9253710>],\n",
       " <a list of 5 Text xticklabel objects>)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How sensitive is k-NN classification accuracy to the choice of the 'k' parameter\n",
    "k_range = range(1, 20)\n",
    "scores = []\n",
    "\n",
    "for k in k_range:\n",
    "    knn = KNeighborsClassifier(n_neighbors = k)\n",
    "    knn.fit(X_train, y_train)\n",
    "    scores.append(knn.score(X_test, y_test))\n",
    "plt.figure()\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('accuracy')\n",
    "plt.scatter(k_range, scores)\n",
    "plt.xticks([0,5,10,15,20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How sensitive is k-NN classification accuracy to the train/test split proportion\n",
    "t = [0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2]\n",
    "knn = KNeighborsClassifier(n_neighbors = 5)\n",
    "plt.figure()\n",
    "for s in t:\n",
    "    scores = []\n",
    "    for i in range(1, 1000):\n",
    "        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 1-s)\n",
    "        knn.fit(X_train, y_train)\n",
    "        scores.append(knn.score(X_test, y_test))\n",
    "    plt.plot(s, np.mean(scores), 'bo')\n",
    "\n",
    "plt.xlabel('Training set proportion (%)')\n",
    "plt.ylabel('accuracy');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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